df <- readr::read_csv("DOHMH_New_York_City_Restaurant_Inspection_Results.csv")
#str(df)

library(plotly)
library(forcats)
library(wordcloud2)
library(tm)
library(tidytext)
library(DT)
library(corpus)
library(dplyr)

#replace NA from "Action" column
df$ACTION = ifelse(is.na(df$ACTION),"Not yet received an inspection",df$ACTION)


#####Just for histogram......
f <- list(
  family = "Courier New, monospace",
  size = 18,
  color = "#7f7f7f"
)
x <- list(
  title = "",
  titlefont = f
) 

df%>%filter(ACTION!="Not yet received an inspection" & ACTION!= "No violations were recorded at the time of this inspection.")%>%select(`CUISINE DESCRIPTION`)%>%plot_ly(x = ~`CUISINE DESCRIPTION`,alpha = 0.6,type = "histogram")%>%layout(xaxis = x)

#####restaurant with violations bar chart vertical
  
df%>%filter(ACTION!="Not yet received an inspection" & ACTION!= "No violations were recorded at the time of this inspection.")%>%select(DBA)%>%count(DBA,sort = TRUE)%>%mutate(DBA = fct_reorder(DBA, n))%>%top_n(20)%>%plot_ly(x = ~n, y = ~DBA ,type = 'bar', orientation = 'h')

#### just try bubble chart
df%>%filter(ACTION!="Not yet received an inspection" & ACTION!= "No violations were recorded at the time of this inspection.")%>%count(DBA)%>%top_n(20)%>%rename(restaurant=DBA, freq = n)%>%
plot_ly(x = ~restaurant, y = ~freq, type = 'scatter', mode = 'markers',color = ~freq/50,colors = 'Reds',marker = list(size = ~freq/50, opacity = 0.5)) %>%
  layout(title = 'Top 20 violation restaurant',
         xaxis = list(showgrid = FALSE),
         yaxis = list(showgrid = FALSE))

#Grade 
df%>%plot_ly(x = ~GRADE)

#score grade box plot
df%>%plot_ly( x = ~GRADE, y = ~SCORE, color = ~GRADE,type = "box")

#viloation description
df%>%select(`VIOLATION DESCRIPTION`)%>%count(`VIOLATION DESCRIPTION`,sort = TRUE)%>%plot_ly(x = ~`VIOLATION DESCRIPTION`, y =~n ,type = "bar")

####word cloud
viloation<-df%>%filter(ACTION!="Not yet received an inspection" & ACTION!= "No violations were recorded at the time of this inspection." & `CRITICAL FLAG`=="Critical")


vio_corpus <- VCorpus(VectorSource(viloation$`VIOLATION DESCRIPTION`))%>%
  tm_map(content_transformer(tolower))%>%
  tm_map(removePunctuation)%>%
  tm_map(removeNumbers)%>%
  tm_map(removeWords, stopwords("english"))%>%
  tm_map(stripWhitespace)
  #tm_map(stemDocument)



tdm <- TermDocumentMatrix(vio_corpus)
tdm.tidy <- tidy(tdm)
viola <- summarise(group_by(tdm.tidy,term),sum(count))
top_50  <- viola %>% top_n(100)
wordcloud2(top_50,color='random-light',
           size=0.5,shape = 'star')